Systems and methods for managing the configuration and execution of executable controls

Abstract

Embodiments of the present disclosure include systems and methods for managing the configuration and execution of executable controls. In particular, a control execution management system may enable organizations to configure executable controls relating to certain internal and/or external processes, and for configuration and execution data for the executable controls to be maintained by the organizations, for example, in a distributed ledger (e.g., a blockchain network). Continuously monitoring configuration and execution data of the executable controls may enable an organization to always have updated information relating to the executable controls and how they impact their associated internal and/or external processes, thereby enabling the organization to, for example, provide such information to regulatory agencies, relevant stakeholders, and so forth.

The invention claimed is: 
     
       1. A control execution management network, comprising:
 one or more computing devices comprising one or more processors configured to execute instructions stored in memory of the one or more computing devices, wherein the instructions, when executed by the one or more processors, are configured to cause the one or more computing devices to:
 continuously monitor one or more processes being performed by one or more user computing devices communicatively connected to a communication network maintained by an organization to detect data relating to configuration and/or execution of one or more executable controls being utilized by the one or more processes, wherein the detected data relating to the configuration and/or the execution of the one or more executable controls comprises data relating to the execution of the one or more executable controls that is performed by the one or more processes via the one or more user computing devices, and wherein the one or more executable controls are configured to provide one or more rules for performance of one or more functions of the one or more processes; 
 determine if the detected data relating to the execution of the one or more executable controls indicates that performance of the one or more functions of the one or more processes violates the one or more rules provided by the one or more executable controls; and 
 automatically store the detected data relating to the configuration and/or the execution of the one or more executable controls in a distributed ledger in response to a determination that the performance of the one or more functions of the one or more processes violates the one or more rules provided by the one or more executable controls. 
 
 
     
     
       2. The control execution management network of  claim 1 , wherein the detected data relating to the configuration and/or the execution of the one or more executable controls comprises data relating to a change in the configuration of the one or more executable controls that is implemented via the one or more user computing devices. 
     
     
       3. The control execution management network of  claim 1 , comprising one or more artificial intelligence (AI) bots configured to:
 continuously monitor the one or more processes being performed by the one or more user computing devices communicatively connected to the communication network to detect the data relating to the configuration and/or the execution of the one or more executable controls being utilized by the one or more processes; and 
 automatically communicate the detected data relating to the configuration and/or the execution of the one or more executable controls to the one or more computing devices. 
 
     
     
       4. The control execution management network of  claim 3 , wherein the one or more AI bots are configured to initiate performance of the one or more processes to detect test data relating to execution of the one or more executable controls being utilized by the one or more processes. 
     
     
       5. The control execution management network of  claim 3 , wherein the one or more computing devices are configured to train each AI bot of the one or more AI bots based on a respective analysis focus of the respective AI bot. 
     
     
       6. The control execution management network of  claim 1 , wherein the one or more executable controls are configured to be utilized by a plurality of processes being performed by a plurality of user computing devices communicatively connected to the communication network. 
     
     
       7. The control execution management network of  claim 1 , wherein the distributed ledger comprises a blockchain network. 
     
     
       8. The control execution management network of  claim 1 , wherein the control execution management network is inaccessible to user computing devices not directly associated with the organization. 
     
     
       9. A method, comprising:
 deploying one or more artificial intelligence (AI) bots of a control execution management system onto a communication network maintained by an organization; 
 continuously monitoring, via the one or more AI bots of the control execution management system, one or more processes being performed by one or more user computing devices communicatively connected to the communication network to detect data relating to configuration and/or execution of one or more executable controls being utilized by the one or more processes, wherein the one or more executable controls are configured to provide one or more rules for performance of one or more functions of the one or more processes; 
 automatically communicating, via the one or more AI bots, the detected data relating to the configuration and/or the execution of the one or more executable controls to one or more computing devices of the control execution management system; and 
 automatically storing, via the control execution management system, the detected data relating to the configuration and/or the execution of the one or more executable controls in a distributed ledger. 
 
     
     
       10. The method of  claim 9 , wherein the detected data relating to the configuration and/or the execution of the one or more executable controls comprises data relating to a change in the configuration of the one or more executable controls that is implemented via the one or more user computing devices. 
     
     
       11. The method of  claim 9 , wherein the detected data relating to the configuration and/or the execution of the one or more executable controls comprises data relating to the execution of the one or more executable controls that is performed by the one or more processes via the one or more user computing devices. 
     
     
       12. The method of  claim 11 , comprising:
 determining, via the control execution management system, if the detected data relating to the execution of the one or more executable controls indicates that performance of the one or more functions of the one or more processes violates the one or more rules provided by the one or more executable controls; and 
 automatically storing, via the control execution management system, the detected data relating to the execution of the one or more executable controls in the distributed ledger in response to a determination that the performance of the one or more functions of the one or more processes violates the one or more rules provided by the one or more executable controls. 
 
     
     
       13. The method of  claim 9 , comprising initiating, via the one or more AI bots, performance of the one or more processes to detect test data relating to execution of the one or more executable controls being utilized by the one or more processes. 
     
     
       14. The method of  claim 9 , comprising training, via the one or more computing devices of the control execution management system, each AI bot of the one or more AI bots based on a respective analysis focus of the respective AI bot. 
     
     
       15. The method of  claim 9 , comprising utilizing the one or more executable controls during performance of a plurality of processes being performed by a plurality of user computing devices communicatively connected to the communication network. 
     
     
       16. The method of  claim 9 , wherein the distributed ledger comprises a blockchain network. 
     
     
       17. A control execution management network, comprising:
 one or more user computing devices communicatively connected to a communication network maintained by an organization, wherein each computing device of the one or more user computing devices comprises one or more processors configured to execute instructions stored in memory of the respective computing device; and 
 one or more artificial intelligence (AI) bots configured to:
 continuously monitor one or more processes being performed by the one or more user computing devices to detect data relating to configuration and/or execution of one or more executable controls being utilized by the one or more processes, wherein the one or more executable controls are configured to provide one or more rules for performance of one or more functions of the one or more processes; and 
 automatically communicate the detected data relating to the configuration and/or the execution of the one or more executable controls to one or more computing devices, and to instruct the one or more computing devices to store the detected data relating to the configuration and/or the execution of the one or more executable controls in a distributed ledger. 
 
 
     
     
       18. The control execution management network of  claim 17 , wherein the one or more AI bots are configured to initiate performance of the one or more processes to detect test data relating to execution of the one or more executable controls being utilized by the one or more processes. 
     
     
       19. The control execution management network of  claim 17 , wherein the one or more computing devices are configured to train each AI bot of the one or more AI bots based on a respective analysis focus of the respective AI bot.